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Benchmark results against native framework's augmentations? #67

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1duo opened this issue Jul 24, 2018 · 4 comments
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Benchmark results against native framework's augmentations? #67

1duo opened this issue Jul 24, 2018 · 4 comments
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@1duo
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1duo commented Jul 24, 2018 •
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Hi,

Is there any published benchmark results available against native frameworks TensorFlow, PyTorch, MxNet?
Given same amount of data augmentations on same hardware. Either full training speed (images/sec) or data augmentations only.
@1duo 1duo changed the title Benchmark Results against native framework's augmentations? Benchmark results against native framework's augmentations? Jul 24, 2018
@JanuszL JanuszL added the question Further information is requested label Jul 25, 2018
@JanuszL
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JanuszL commented Jul 25, 2018

Hi,
We don't have anything available for publishing regarding performance. We plan to provide such numbers soon. You can check preliminary results for DGX-2 mentioned during talk about DALI slides, video. It is definitely on our ToDo list.
Also please keep in mind that DALI alleviates workloads that are CPU bound - multiple GPU or limited number of CPU cores for each GPU. When your CPU can catch up with GPU (simple pipeline or low GPU number comparing to CPU cores) there is no performance benefit from DALI.

@1duo
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1duo commented Jul 25, 2018

@JanuszL Thanks!

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JanuszL commented Jul 26, 2018

Internally tracked DALI-174.

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JanuszL commented May 8, 2019

You can check this results in our last GTC19 presentation.

@JanuszL JanuszL closed this as completed May 8, 2019
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